Data mining (DM) refers to a nontrivial process of revealing information that is implicit, previously unknown, and potentially valuable from a large amount of data in a database. DM is mainly based on artificial intelligence, machine learning, pattern recognition, statistics, a database, visualization technologies, and the like, analyzes enterprise data in a highly automated manner, makes an inductive inference, and mines for a potential pattern of the enterprise data, to help a decider to adjust a marketing strategy, reduce risks, and make a correct decision.
However, with the arrival of the age of big data, sources of objects on which data mining is performed are increasingly extensive, and consequently, a quantity of samples and/or a quantity of feature columns in a data set reaches a very large scale. In the prior art, after feature column selection is performed and if there are excessive selected feature columns, a problem of resource insufficiency such as a memory shortage occurs in which causes a failure in execution of a data mining process.